Coping with a diagnosis of Alzheimer's disease: A client and caregiver perspective

The purpose of this study was to examine how individuals and their caregivers cope with a diagnosis of Alzheimer's disease. The sample size consisted of six patients with Alzheimer's disease and seven caregivers. The caregivers included spouses and adult children. The study was conducted at an academic medical center in the South Florida area. Using a phenomenological approach, data were collected by audiotaped interviews. Data were analyzed following the seven steps of Colaizzi (1978).^ The results of the study indicated that clients experienced fear, social withdrawal, decreased self-esteem and a need for love and support. Caregivers experienced psychological strain, burden, lifestyle adjustments and sacrifice. Both clients and caregivers identified numerous strategies for coping with Alzheimer's disease. The findings reflect the need for a holistic approach to promoting the quality of life for patients and caregivers. ^

Multidimensional classification and diagnosis of leukemia in flow cytometry

This research is to establish new optimization methods for pattern recognition and classification of different white blood cells in actual patient data to enhance the process of diagnosis. Beckman-Coulter Corporation supplied flow cytometry data of numerous patients that are used as training sets to exploit the different physiological characteristics of the different samples provided. The methods of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used as promising pattern classification techniques to identify different white blood cell samples and provide information to medical doctors in the form of diagnostic references for the specific disease states, leukemia. The obtained results prove that when a neural network classifier is well configured and trained with cross-validation, it can perform better than support vector classifiers alone for this type of data. Furthermore, a new unsupervised learning algorithm---Density based Adaptive Window Clustering algorithm (DAWC) was designed to process large volumes of data for finding location of high data cluster in real-time. It reduces the computational load to ∼O(N) number of computations, and thus making the algorithm more attractive and faster than current hierarchical algorithms.

Obesity Indicators by Race/Ethnicity for Diagnosis of Cardiometabolic Diseases for a US Representative Sample of Adults

Background: Obesity, a growing epidemic, is a preventable risk factor for cardiometabolic diseases. Obesity and cardiometabolic diseases affect Hispanics and African Americans more than non-Hispanic Caucasians. This study examined the relationship among race/ethnicity, obesity diagnostic measures (body mass index, waist circumference, subscapular and triceps skinfold thickness), and cardiometabolic risk factors (hyperglycemia, high, non-high-density lipoprotein cholesterol, low, high-density lipoprotein cholesterol, and hypertension) for adults across the United States. Methods: Using data from two-cycles of the National Health and Examination Survey (NHANES) 2007-2010, and accounting for the complex sample design, logistic regression models were conducted comparing obesity indicators in Mexican Americans, other Hispanics, and Black non-Hispanics, with White non-Hispanics and their associations with the presence of cardiometabolic diseases. Results: Differences by race/ethnicity were found for subscapular skinfold thickness and hyperglycemia. Waist circumference and subscapular skinfold were positively associated with the presence of hyperglycemia; dyslipidemia, and hypertension across race/ ethnicity, adjusting for age, gender, smoking, physical activity, education, income to poverty index, and health insurance. Race/ ethnicity did not influence the association of any obesity indicators with the tested cardiometabolic diseases. All obesity measures except triceps skinfold were associated with hyperglycemia. Conclusions: We suggest that subscapular skinfold thickness be considered as an inexpensive non-intrusive screening tool for cardiometabolic risk factors in an adult US population